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Purpose: CALGB 40603 (NCT00861705), a 2 × 2 randomized phase II trial, demonstrated that adding carboplatin or bevacizumab to weekly paclitaxel (wP) followed by doxorubicin and cyclophosphamide significantly increased the pathologic complete response (pCR) rate in stage II-III triple-negative breast cancer. We now report long-term outcomes (LTOs) and correlative science end points., Patients and Methods: The Kaplan-Meier method was used to estimate LTOs in 443 patients who initiated study treatment. Log-rank tests and Cox proportional hazards models evaluated the impact of clinical characteristics, pathologic response, calculated residual cancer burden (RCB) in patients with residual disease (RD), treatment assignment, and dose delivery during wP on LTOs, including event-free survival (EFS). Genomic predictors of treatment response and outcomes were assessed on pretreatment tumor samples by mRNA sequencing., Results: Among baseline characteristics, only the clinical stage was associated with LTOs. At a median follow-up of 7.9 years, LTOs were not significantly improved with either carboplatin or bevacizumab, overall or in patients with basal-like subtype cancers by genomic analysis. Patients with pCR (n = 205, 46.3%) had significantly higher 5-year EFS (85.5% v 56.6%, log-rank P < .0001) and overall survival (87.9% v 63.4%, P < .0001) rates compared with patients with RD, even those with RCB class I. Among clinical and genomic features, evidence of immune activation, including tumor-infiltrating lymphocytes and low B-cell receptor evenness, was associated with pCR and improved EFS., Conclusion: Despite higher pCR rates, neither carboplatin nor bevacizumab appeared to improve LTOs although the study was not powered to assess these secondary end points. pCR was associated with superior LTOs even when compared with minimal RD. Markers of immune activation in pretreatment tumor biopsies were independently associated with higher pCR rates and improved survival., Competing Interests: Karla BallmanConsulting or Advisory Role: Medtronic, Takeda, AgenusPatents, Royalties, Other Intellectual Property: Prostate cancer signature patent (Inst)Expert Testimony: Janssen Oncology, Lilly, Sanofi Sara SelitskyEmployment: QuantBio, Sash BiosciencesConsulting or Advisory Role: GeneCentric, C4 Therapeutics, Select ImmunoGenomics, FORMA Therapeutics, Atlas Venture, CytomX Therapeutics (Inst), Actym Therapeutics (Inst), Capulus Therapeutics (Inst), Codagenix (Inst) Joel S. ParkerStock and Other Ownership Interests: GeneCentric, Reveal GenomicsConsulting or Advisory Role: Bristol Myers Squibb/CelgenePatents, Royalties, Other Intellectual Property: J.S.P. has authored patents related to the PAM50 algorithm, which are licensed to NanoString Technologies Patricia A. SpearsConsulting or Advisory Role: Pfizer Sara M. TolaneyThis author is a member of the Journal of Clinical Oncology Editorial Board. Journal policy recused the author from having any role in the peer review of this manuscript.Consulting or Advisory Role: Novartis, Pfizer, Merck, Lilly, Nektar, NanoString Technologies, AstraZeneca, Puma Biotechnology, Genentech, Eisai, Sanofi, Celldex, Bristol Myers Squibb, Paxman, Seattle Genetics, Odonate Therapeutics, AbbVie, Silverback Therapeutics, G1 Therapeutics, OncoPep, Kyowa Hakko Kirin, Samsung Bioepis, CytomX Therapeutics, Daiichi Sankyo, Athenex, Immunomedics/Gilead, Mersana, Certara, 4D Pharma, Ellipses Pharma, OncoSec, Chugai Pharma, BeyondSpring Pharmaceuticals, OncXerna TherapeuticsResearch Funding: Genentech/Roche (Inst), Merck (Inst), Exelixis (Inst), Pfizer (Inst), Lilly (Inst), Novartis (Inst), Bristol Myers Squibb (Inst), Eisai (Inst), AstraZeneca (Inst), NanoString Technologies (Inst), Cyclacel (Inst), Nektar (Inst), Immunomedics (Inst), Odonate Therapeutics (Inst), Sanofi (Inst), Seattle Genetics (Inst)Travel, Accommodations, Expenses: AstraZeneca, Lilly, Merck, Nektar, Novartis, Pfizer, Genentech/Roche, Immunomedics, Eisai, NanoString Technologies, Puma Biotechnology, Celldex Cynthia MaConsulting or Advisory Role: Novartis, Seattle Genetics, Agendia, AstraZeneca, Athenex, Bayer HealthCare Pharmaceuticals, Biovica Inc, Eisai, Olaris, Philips Electronics, Puma Biotechnology, Sanofi Genzyme, Jacobio, Natera, InivataResearch Funding: Pfizer (Inst), Puma Biotechnology (Inst) Eleftherios MamounasHonoraria: Genentech/Roche, Genomic Health, PreciscaConsulting or Advisory Role: Genomic Health, BioTheranostics, Roche/Genentech, Merck, Puma Biotechnology, Precisca, AgendiaSpeakers' Bureau: Genomic Health, Genentech/Roche Mehra GolshanConsulting or Advisory Role: AbbVie, BertisResearch Funding: Breast Cancer Research Foundation Jennifer R. BellonThis author is a member of the Journal of Clinical Oncology Editorial Board. Journal policy recused the author from having any role in the peer review of this manuscript.Leadership: International Journal of Radiation Oncology Biology PhysicsHonoraria: UpToDate, Accuray, Leidos Biomedical Research, Grupo OncoclinicasResearch Funding: NanoString Technologies (Inst)Patents, Royalties, Other Intellectual Property: Coeditor of breast cancer textbook (Radiation Therapy Techniques and Treatment Planning for Breast Cancer). Honorarium, SpringerOther Relationship: Varian Medical Systems Deborah CollyarHonoraria: PfizerConsulting or Advisory Role: Parexel, MaxisIT, Kinnate BiopharmaTravel, Accommodations, Expenses: Parexel Olwen M. HahnLeadership: Via OncologyStock and Other Ownership Interests: Teleflex MedicalHonoraria: Cardinal Health (I)Consulting or Advisory Role: Pfizer, hmpglobal.comTravel, Accommodations, Expenses: Cardinal Health (I) Clifford A. HudisUncompensated Relationships: Alliance Foundation Trials, Columbia University, Memorial Sloan-Kettering Cancer CenterOpen Payments Link: https://openpaymentsdata.cms.gov/physician/471974/summary Eric P. WinerHonoraria: Genentech/Roche, Genomic HealthConsulting or Advisory Role: Leap Therapeutics, Seattle Genetics, Jounce Therapeutics, GlaxoSmithKline, Carrick Therapeutics, Lilly, G1 Therapeutics, Syros Pharmaceuticals, Genentech/Roche, Gilead Sciences, Zymeworks, AthenexResearch Funding: Genentech (Inst)Other Relationship: InfiniteMD Ann PartridgePatents, Royalties, Other Intellectual Property: I receive small royalty payments for coauthoring the breast cancer survivorship section of UpToDateOpen Payments Link: https://openpaymentsdata.cms.gov/physician/835197 Terry HyslopConsulting or Advisory Role: AbbVieTravel, Accommodations, Expenses: AbbVie Lisa A. CareyResearch Funding: Syndax (Inst), Novartis (Inst), NanoString Technologies (Inst), AbbVie (Inst), Seattle Genetics (Inst), Veracyte (Inst)Patents, Royalties, Other Intellectual Property: Royalty-sharing agreement, investorship interest in licensed IP to startup company, Falcon Therapeutics, that is designing neural stem-cell–based therapy for glioblastoma multiforme (I)Uncompensated Relationships: Sanofi (Inst), Novartis (Inst), G1 Therapeutics (Inst), Genentech/Roche (Inst), GlaxoSmithKline (Inst), AstraZeneca/Daiichi Sankyo (Inst), Aptitude Health (Inst), Exact Sciences (Inst), EisaiOpen Payments Link: https://openpaymentsdata.cms.gov/physician/179671 Charles M. PerouLeadership: GeneCentricStock and Other Ownership Interests: Bioclassifier, GeneCentric, Reveal GenomicsConsulting or Advisory Role: Bioclassifier, GeneCentric, NanoString Technologies, Veracyte, Reveal GenomicsPatents, Royalties, Other Intellectual Property: Royalties from PAM50 breast cancer gene patent application and from lung gene signature patentTravel, Accommodations, Expenses: Takeda, Chugai Pharma William M. SikovHonoraria: UpToDateSpeakers' Bureau: Lilly, Daiichi Sankyo, Seattle GeneticsNo other potential conflicts of interest were reported.

Inhibition of the HER2/ERBB2 receptor is a keystone to treating HER2-positive malignancies, particularly breast cancer, but a significant fraction of HER2-positive (HER2+) breast cancers recur or fail to respond. Anti-HER2 monoclonal antibodies, like trastuzumab or pertuzumab, and ATP active site inhibitors like lapatinib, commonly lack durability because of adaptive changes in the tumor leading to resistance. HER2+ cell line responses to inhibition with lapatinib were analyzed by RNAseq and ChIPseq to characterize transcriptional and epigenetic changes. Motif analysis of lapatinib-responsive genomic regions implicated the pioneer transcription factor FOXA1 as a mediator of adaptive responses. Lapatinib in combination with FOXA1 depletion led to dysregulation of enhancers, impaired adaptive upregulation of HER3, and decreased proliferation. HER2-directed therapy using clinically relevant drugs (trastuzumab with or without lapatinib or pertuzumab) in a 7-day clinical trial designed to examine early pharmacodynamic response to antibody-based anti-HER2 therapy showed reduced FOXA1 expression was coincident with decreased HER2 and HER3 levels, decreased proliferation gene signatures, and increased immune gene signatures. This highlights the importance of the immune response to anti-HER2 antibodies and suggests that inhibiting FOXA1-mediated adaptive responses in combination with HER2 targeting is a potential therapeutic strategy.

Background: Little is known about the prognostic significance of somatically mutated genes in metastatic melanoma (MM). We have employed a combined clinical and bioinformatics approach on tumor samples from cutaneous melanoma (SKCM) as part of The Cancer Genome Atlas project (TCGA) to identify mutated genes with potential clinical relevance. Methods: After limiting our DNA sequencing analysis to MM samples ( n = 356) and to the CANCER CENSUS gene list, we filtered out mutations with low functional significance (snpEFF). We performed Cox analysis on 53 genes that were mutated in ≥3% of samples, and had ≥50% difference in incidence of mutations in deceased subjects versus alive subjects. Results: Four genes were potentially prognostic [ RAC1, FGFR1, CARD11, CIITA ; false discovery rate (FDR) < 0.2]. We identified 18 additional genes (e.g., SPEN, PDGFRB, GNAS, MAP2K1, EGFR, TSC2 ) that were less likely to have prognostic value (FDR < 0.4). Most somatic mutations in these 22 genes were infrequent (< 10%), associated with high somatic mutation burden, and were evenly distributed across all exons, except for RAC1 and MAP2K1 . Mutations in only 9 of these 22 genes were also identified by RNA sequencing in >75% of the samples that exhibited corresponding DNA mutations. The low frequency, UV signature type and RNA expression of the 22 genes in MM samples were confirmed in a separate multi-institution validation cohort ( n = 413). An underpowered analysis within a subset of this validation cohort with available patient follow-up ( n = 224) showed that somatic mutations in SPEN and RAC1 reached borderline prognostic significance [log-rank favorable ( p = 0.09) and adverse ( p = 0.07), respectively]. Somatic mutations in SPEN , and to a lesser extent RAC1 , were not associated with definite gene copy number or RNA expression alterations. High (>2+) nuclear plus cytoplasmic expression intensity for SPEN was associated with longer melanoma-specific overall survival (OS) compared to lower (≤ 2+) nuclear intensity ( p = 0.048). We conclude that expressed somatic mutations in infrequently mutated genes beyond the well-characterized ones (e.g., BRAF, RAS, CDKN2A, PTEN, TP53 ), such as RAC1 and SPEN , may have prognostic significance in MM.

Purpose: Response to a complex trastuzumab-based regimen is affected by multiple features of the tumor and its microenvironment. Developing a predictive algorithm is key to optimizing HER2-targeting therapy. Experimental Design: We analyzed 137 pretreatment tumors with mRNA-seq and DNA exome sequencing from CALGB 40601, a neoadjuvant phase III trial of paclitaxel plus trastuzumab with or without lapatinib in stage II to III HER2-positive breast cancer. We adopted an Elastic Net regularized regression approach that controls for covarying features within high-dimensional data. First, we applied 517 known gene expression signatures to develop an Elastic Net model to predict pCR, which we validated on 143 samples from four independent trials. Next, we performed integrative analyses incorporating clinicopathologic information with somatic mutation status, DNA copy number alterations (CNA), and gene signatures. Results: The Elastic Net model using only gene signatures predicted pCR in the validation sets (AUC = 0.76). Integrative analyses showed that models containing gene signatures, clinical features, and DNA information were better pCR predictors than models containing a single data type. Frequently selected variables from the multiplatform models included amplifications of chromosome 6p, TP53 mutation, HER2-enriched subtype, and immune signatures. Variables predicting resistance included Luminal/ER + features. Conclusions: Models using RNA only, as well as integrated RNA and DNA models, can predict pCR with improved accuracy over clinical variables. Somatic DNA alterations (mutation, CNAs), tumor molecular subtype (HER2E, Luminal), and the microenvironment (immune cells) were independent predictors of response to trastuzumab and paclitaxel-based regimens. This highlights the complexity of predicting response in HER2-positive breast cancer. Clin Cancer Res; 24(21); 5292-304. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Pulmonary large-cell neuroendocrine carcinomas (LCNECs) have similarities with other lung cancers, but their precise relationship has remained unclear. Here we perform a comprehensive genomic (n = 60) and transcriptomic (n = 69) analysis of 75 LCNECs and identify two molecular subgroups: "type I LCNECs" with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and "type II LCNECs" enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1 high /DLL3 high /NOTCH low , type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1 low /DLL3 low /NOTCH high , and an upregulation of immune-related pathways. In conclusion, LCNECs comprise two molecularly defined subgroups, and distinguishing them from SCLC may allow stratified targeted treatment of high-grade neuroendocrine lung tumors.

Background: Papillary renal-cell carcinoma, which accounts for 15 to 20% of renal-cell carcinomas, is a heterogeneous disease that consists of various types of renal cancer, including tumors with indolent, multifocal presentation and solitary tumors with an aggressive, highly lethal phenotype. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist., Methods: We performed comprehensive molecular characterization of 161 primary papillary renal-cell carcinomas, using whole-exome sequencing, copy-number analysis, messenger RNA and microRNA sequencing, DNA-methylation analysis, and proteomic analysis., Results: Type 1 and type 2 papillary renal-cell carcinomas were shown to be different types of renal cancer characterized by specific genetic alterations, with type 2 further classified into three individual subgroups on the basis of molecular differences associated with patient survival. Type 1 tumors were associated with MET alterations, whereas type 2 tumors were characterized by CDKN2A silencing, SETD2 mutations, TFE3 fusions, and increased expression of the NRF2-antioxidant response element (ARE) pathway. A CpG island methylator phenotype (CIMP) was observed in a distinct subgroup of type 2 papillary renal-cell carcinomas that was characterized by poor survival and mutation of the gene encoding fumarate hydratase (FH)., Conclusions: Type 1 and type 2 papillary renal-cell carcinomas were shown to be clinically and biologically distinct. Alterations in the MET pathway were associated with type 1, and activation of the NRF2-ARE pathway was associated with type 2; CDKN2A loss and CIMP in type 2 conveyed a poor prognosis. Furthermore, type 2 papillary renal-cell carcinoma consisted of at least three subtypes based on molecular and phenotypic features. (Funded by the National Institutes of Health.).

Background: Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas., Methods: We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes., Results: Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma., Conclusions: The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07-0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11-1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion.